Hello boys and girls, looking forward to know more about MongoDB indexes?

Today we’ll talk about Multikey indexes. Yeah, only about them because it’s quite a big topic. I also wanted to cover text indexes, but they are too cool to talk about them in the same post, they deserve their own %)

As you may know, PostgreSQL provides you four index types: B-tree, Hash, GiST and GIN. They all named the way that if you don’t know ’em you’ll never get which one do you need. In MongoDB indexes are named in a more human-readable way. Here they are:
1. Single field index.
2. Compound index.
3. Multikey index.
4. Text index.
5. Hashed index.
6. 2dsphere, 2d, geoHaystack indexes.

Since I’m using Mongo for more than a year now, I worked with few of them and will elucidate you the most commonly used ones.

Not a long time ago I had no idea about what is the tool named Terraform. It was just beyond my bounds of interests and problems. But a month ago I changed a company and then had to deal with it. And guys, it’s wow. It’s so amazing thing so I even started liking DevOps job.

In a few words, it’s a tool to do infrastructure as a code. As they say on their website “Terraform enables you to safely and predictably create, change, and improve production infrastructure”.

In this post, I’ll cover why may you (as a developer or a DevOps) need it and how to get started. Getting started will be not just a hello world, but a real example, you can try right away.

Past weeks I was in process of moving to another city and had no time to spend it for cool technical things, but I had a time for past experience reflection. About one thing I used frequently in past time I want to write here. As you can see, the topic is about Pair Programming.

My main tool for every day is Ruby, but a few months ago I started using Python for playing with data. I heard a lot that Python is heavily used by Data Scientists and scientists in general, but I didn’t expect that even for not a python-experienced developer it can give so much power. So today I want to briefly introduce you Python’s library pandas.